Title:
Using Pathway Logic to Integrate Signal Transduction and Gene Expression Data
Authors:
Linda Briesemeister (1), Joe Gray (2), Laura Heiser (2), Merrill Knapp (1), Keith Laderoute (1), Andy Poggio (1), Paul Spellman (1), Carolyn Talcott (1*)
(1) SRI International, (2) Lawrence Berkeley National Laboratory
(*) Contact author: carolyn.talcott@gmail.com
Abstract:
Pathway Logic (http://pl.csl.sri.com/) is an approach to the modeling
and analysis of molecular and cellular processes based on rewriting
logic. A Pathway Logic knowledge base includes data types
representing cellular components such as proteins, small molecules,
complexes, compartments/locations, protein state, and
post-translational modifications. Rewrite rules describe the behavior
of proteins and other components depending on modification state and
biological context. Each rule represents a step in a biological
process such as metabolism or intra/inter- cellular signaling. A
collection of such facts forms a formal knowledge base. Logical
inference and analysis techniques are used for simulation to study
possible ways a system could evolve, to assemble pathwayse as answers
to queries, and to reason about dynamic assembly of complexes,
cascading transmission of signals, feedback-loops, cross talk between
subsystems, and larger pathways.
The poster will illustrate the use of the Pathway Logic knowledge base
in combination with statistical methods to analyze gene expression
data obtained from a collection of breast cancer cell lines. From the
gene expression data for a cell line, a network of potentially
reachable signaling reactions (rules) is extracted from the knowledge
base. These networks of rules are clustered to find small signaling
modules whose elements appear together or are absent together in the
networks for the different cell lines. The impact of a set of proteins
on signaling network can be represented as a subnetwork, viewed alone
or in context. This has been used to analyze the impact on the Efg
signaling network of genes whose presence/absence differs across the
cell lines. In addition, use of a tool developed to visualize change
of gene expression levels in cells at different time points after
treatment will be illustrated using the Wnt pathway and time course
data from treatment of one of the cell lines.
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